Estimation of the channel conditions between the transmitter and receiver is a necessary step for many communications systems to enable detection and optimal processing of a data stream received from a signal source. So as to enable the necessary channel estimations, most of these systems embed reference symbols in the data stream that are known a priori to the receiver.
For channel estimation in frequency-multiplexed communication systems that include a plurality of frequency subcarriers, receivers typically estimate the channel response using a single complex coefficient for each subcarrier. Sometimes, these channel estimates are averaged or smoothed over groups of adjacent frequency subcarriers so as to reduce the error, under a “static” assumption that the channel coefficients will be substantially constant within the groups of frequency subcarriers. This smoothing approach is effective, but is typically limited by variations in the channel coefficients as a function of subcarrier frequency, which limits the number of adjacent frequency subcarriers for which the static assumption will be valid.
With reference to FIG. 1, in some cases, joint channel estimation techniques are necessitated by the presence of multiple, simultaneous data streams received over the same frequency subcarriers from multiple signal sources, for example due to multiple access interference (i.e. a plurality of users 100 transmitting a plurality of signals 102 to a base station 104 over the same communication channels) and/or Multiple Input Multiple Output (“MIMO”) multi-path propagation. The need for joint channel estimation can be even greater in a Cloud Radio Access Network (“C-RAN”). These joint channel estimation techniques attempt to obtain multiple channel estimates simultaneously from signals transmitted by multiple signal sources, thereby improving the channel estimation accuracy when the reference symbols from multiple signal sources are not orthogonal.
Typically, the number of reference symbol samples used for joint channel estimation must be greater than the number of channel estimates to be computed. With reference to FIG. 2, in the case of frequency-multiplexed data transmissions, such as Orthogonal Frequency Division Multiplexing (“OFDM”) or Single Channel-Frequency Domain Multiple Access (“SC-FDMA”) 202 encoded transmissions, each data stream 200 is split into a plurality of α sub-streams 204 that are converted to a time domain signal by an Inverse Fast Fourier Transform (“IFFT”) 206 and transmitted 102 over frequency “subcarriers.” In such cases, pluralities of reference symbol samples that are distributed across groups of frequency subcarriers can be included in the joint channel estimation, so long as the “static assumption” remains valid. Note that some or all of the signal sources may not use all of the a frequency subcarriers 204 that are included in the data transmission.
Accordingly, the number of signal sources for which channel coefficients can be accurately estimated is generally limited by the “static assumption,” i.e. by the number of adjacent frequency subcarriers over which the channel coefficients can be assumed to be constant. For example, in systems operating according to the LTE standard, the channel coefficient for each signal source is usually assumed to be constant over 12 frequency subcarriers (one “Resource Block”). This generally limits the dimensionality of a linear estimator (e.g. a least squares estimator) to 12. If more than 12 signal sources simultaneously use the same 12 frequency subcarriers, then the coefficient estimates are likely to degenerate severely.
What is needed, therefore, is an improved channel estimation method and system for frequency-multiplexed data transmissions that overcome the limitations imposed by the static assumption and thereby increase the accuracy of channel estimations and the number of signal sources to which joint channel estimation can be applied.